3 years February, July and October
RM45,600 Malaysian student
RM53,280 International student 2025 fees per year
Professionally accredited Industrial training
CAREER PATHS Graduates with data science skills are in high demand. Possible careers could include:
• big data engineer
• business intelligence developer
• chief technology officer
• data scientist
• data architect
• data engineer
• data analyst
• machine learning specialist
• research scientist
• software developer
• statistician.
You’ ll be able to work in a wide range of industries, such as:
• digital humanities
• consulting
• cybersecurity
• law
• scientific research
• marketing
• robotics
• engineering
• business analytics
• banking.
BACHELOR OF COMPUTER SCIENCE IN DATA SCIENCE
KPT / JPT( R / 0613 / 6 / 0076) 09 / 29- MQA / FA12435
This is the era of big data and artificial intelligence. Data science represents a cutting-edge discipline which applies scientific methods, mathematics, algorithms and artificial intelligence to extract and visualise intelligent insights from huge volumes of data.
In the fast-progressing world of the Information Age these insights, whether delivered via autonomous integrated systems or in traditional reports, have the potential to fuel innovation and transform decision making. Data scientists deal with the challenges of big data – its interpretation, management and use – in fields as diverse as marketing, information systems, engineering, finance, arts, humanities, science and medicine.
Monash brings a breadth of expertise to bear on issues relating to big data. If you aspire to solve real-world problems based on the information challenges of big data, then specialising in data science will equip you with the practical skills to excel in your chosen career.
Professionally accredited
This course is accredited by the Australian Computer Society.
Areas of study
• Mathematical statistics
• Principles of data science
• Modelling for data analysis
• Business intelligence and data warehousing
• Data analytics and visualisation
• Big data management and processing
• Deep learning and artificial intelligence
• Malicious AI and dark side security.
What you’ ll learn
Studying data science, your learning experience will cover:
• technical skills in areas such as programming and databases
• modelling, visualisation and analysis, including using graphics and interactive visualisations for professional practice
• legal and ethical issues associated with collecting and interpreting data, and how to respond to them
• advanced data science knowledge via electives, including machine learning and deep learning, business applications of data science, big data management and countering malicious cyberattacks
• soft skills in communication, key to conveying your findings to future stakeholders.
Course structure
This course consists of 14 compulsory( core) units in computer science, data science and mathematics, two restricted electives chosen from an approved list of data science topics, eight free elective units, and an industry attachment. The free electives can be taken as a sequence in a specific field of study within the school or from a discipline offered by another school. A capstone project spanning both semesters of the third year concludes your studies.
Elective units
LEVEL ONE
• Introduction to software engineering
• Programming fundamentals in Java
LEVEL TWO
• Operating systems
• Object-oriented design and implementation
• Mobile application development
• Introduction to cybersecurity
• Programming paradigms
• Software quality and testing
• Software engineering process and management
LEVEL THREE
• Computer architecture
• Deep learning
• Advanced data structures and algorithms
• Artificial Intelligence
• Software engineering: Architecture and design
• Big data management and processing
• Business intelligence and data warehousing
• Malicious AI and dark side security
• Parallel computing
• Industry-based learning( equivalent to three units, i. e. 18 points of level three elective units).
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